Re:Show HN: Using classic dev books to guide AI agents
by YaraDori on Sunday February 22, 2026 @05:30PM
(#47115460)
Cool idea — “book as rubric” is a nice way to avoid vague self-critiques.
One thing I’ve found helps keep agent review loops from getting shallow is to separate levels of critique:
1) a fast “lint” pass (format, obvious bugs, missing tests)
2) a domain pass that’s forced to cite specific passages/rules from the rubric
3) a “counterexample” pass: reviewer must propose at least 1 concrete failing scenario + how to reproduce
Question: are you capturing the reviewer’s evidence (links, excerpts, failing cases) in a structured log so a human can audit why the agent changed something?
Related: I’m working on SkillForge (https://skillforge.expert) — we’ve been thinking about similar auditability, but for UI workflows: record once, then replay with checkpoints + retries, so humans approve at meaningful boundaries instead of every click.
One thing I’ve found helps keep agent review loops from getting shallow is to separate levels of critique: 1) a fast “lint” pass (format, obvious bugs, missing tests) 2) a domain pass that’s forced to cite specific passages/rules from the rubric 3) a “counterexample” pass: reviewer must propose at least 1 concrete failing scenario + how to reproduce
Question: are you capturing the reviewer’s evidence (links, excerpts, failing cases) in a structured log so a human can audit why the agent changed something?
Related: I’m working on SkillForge (https://skillforge.expert) — we’ve been thinking about similar auditability, but for UI workflows: record once, then replay with checkpoints + retries, so humans approve at meaningful boundaries instead of every click.